Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Событийный анализ (CAR и BHAR)× | Регрессия методом обыкновенных наименьших квадратов (ОНМК)× | |
|---|---|---|
| Область≠ | Финансы | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1997 | 2019 |
| Автор метода≠ | MacKinlay (review); Kothari & Warner (econometrics) | Wooldridge (textbook treatment); classical least squares |
| Тип≠ | Abnormal-return model for financial events | Linear regression |
| Основополагающий источник≠ | MacKinlay, A. C. (1997). Event Studies in Economics and Finance. Journal of Economic Literature, 35(1), 13–39. link ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Другие названия≠ | event study, cumulative abnormal return analysis, abnormal return analysis, CAR | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Связанные≠ | 4 | 5 |
| Сводка≠ | The event study is a financial research method that measures the impact of a news release, policy change, or corporate event on asset prices through cumulative abnormal returns. Reviewed by MacKinlay (1997) and formalised econometrically by Kothari and Warner (2007), it is the standard tool for testing the efficient-market hypothesis and analysing the information content of events. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateНабор данных ↗ |
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